JavaScript

Youtube search... ...Google search

• 11 Javascript Machine Learning Libraries for 2019 | Jonathan Saring - Bits and Pieces Medium
• 10 Javascript IoT Libraries To Use In Your Next Project | Jonathan Saring
• A Web Developer's Guide to Machine Learning in JavaScript | Robin Wieruch
• Neural networks in JavaScript - Brain.js | Robert Plummer
• Machine Learning in Node.js With TensorFlow.js | James Thomas
• Visualization

A sampling of available Javascript Machine Learning libraries

• Libraries for NLP see Natural Language Tools & Services
• TensorFlow.js for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs)
  • Keras.js No longer active - capability now is in TensorFlow.js
  • Deeplearnjs rebranded to TensorFlow.js
• Tensorflow Deep Playground; written in Typescript using d3.js
• brain.js in browser and Node.js ..see introduction
• Natural provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, tf-idf, WordNet, string similarity, some inflections, and more. (nodejs)
• Neuro.js Learning to Drive project a deep learning and reinforcement learning Javascript library framework for the browser. Implementing a full stack neural-network based machine learning framework with extended reinforcement-learning support
• TensorFire is a framework for running neural networks in the browser, accelerated by WebGL
• Conventjs (not maintained)] neural networks supporting common modules, classification, Regression, an experimental Reinforcement Learning module, able to train convolutional networks that process images
• ConvNetJS an NPM version is also available for those using Node.js, and the library is designed to make proper use of JavaScript’s asynchronicity.
• mljs includes supervised and unsupervised learning, artificial neural networks, Regression algorithms and supporting libraries for statistics, math etc.
• Synaptic multilayer perceptrons, multilayer long-short term memory networks, liquid state machines and a trainer capable of training a verity of networks
• Webdnn this framework optimizes the DNN model to compress the model data and accelerate execution through JavaScript APIs such as WebAssembly and WebGPU
• Neataptic neuro-evolution & backpropagation for the browser
• Mind make predictions, using a matrix implementation to process training data and enabling configurable network topology.
• DeeForge a development environment for deep learning
• MXnet.js deep learning in browser (without server); allows you to mix symbolic and imperative programming on the fly with a graph optimization layer for performance

Graphics

• Visualization with Python and underlying Javascript libraries
• D3js.org - D3.js v4 Force Directed Graph with Labels
  • TensorFlow Deep Playground an interactive visualization of neural networks, written in TypeScript using d3.js and can be repurposed for different means
• WebGL.js - (Web Graphics Library) is a JavaScript API for rendering interactive 3D and 2D graphics within any compatible web browser without the use of plug-ins
• Knowledge Graphs
  • Graphs Are Fundamental to Modern AI Systems | neo4j
  • Why Knowledge Graphs Are Foundational to Artificial Intelligence | Jim Webber
  • Creating The Most Sophisticated Recommendations Using Native Graphs | Emil Eifrem
  • Neo4j Machine Learning Extensions
  • Review prediction with Neo4j and TensorFlow | David Mack

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• Git - GitHub and GitLab
• Bit

Node.js

Youtube search...

• Watch me Build a Marketing Startup | Siraj Raval

Demos

• Land Lines
• Learning to Drive
• TensorFlow.js Demos